def run(self):
while True:
start = self.env.now
# First look up the metadata
if self.lookup_time > 0:
lookup_req = self.hdfs.get_namenode_req(self.client_id, self.lookup_time)
yield lookup_req.submit()
lookup_done = simpy.AllOf(self.env, lookup_req.all_done_list())
yield lookup_done
# Then read the data
if self.read_size > 0:
read_req, done_evt = self.hdfs.get_read_req(self.client_id, self.read_size)
yield read_req.submit()
yield done_evt
# Then write
if self.write_size > 0:
write_req, ack_done = self.hdfs.get_write_req(None, self.client_id, self.write_size)
yield write_req.submit()
yield ack_done
latency = self.env.now - start
self.num_reqs += 1 # a lookup + a read + a write counts as one req
self.total_latency += latency
if self.think_time != 0:
yield self.env.timeout(self.think_time)
def reset_and_sim(self, policies): self.simpy_env = simpy.Environment() self.done = False self.fire_extinguish_events = [simpy.Event(self.simpy_env) for i in range(self.n_fires)] fire_levels = [] for i, n in enumerate(self.num_fires_of_each_size): fire_levels += [i+1] * n if self.fire_locations is not None: self.fires = [ Fire(self, self.simpy_env, i, fire_levels[i], fl) for i, fl in enumerate(self.fire_locations) ] else: # we want to randomize fire_locations = ( 2.*np.random.random_sample((self.n_fires,2)) - 1.).tolist() self.fires = [ Fire(self, self.simpy_env, i, fire_levels[i], fl) for i, fl in enumerate(fire_locations) ] if self.start_positions is not None: self.env_agents = [ UAV(self, self.simpy_env, i, sp, sp, self.discount, policies[i]) for i,sp in enumerate(self.start_positions) ] else: # we want to randomize start_positions = ( 2.*np.random.random_sample((self.n_agents,2)) - 1.).tolist() self.env_agents = [ UAV(self, self.simpy_env, i, sp, sp, self.discount, policies[i]) for i,sp in enumerate(start_positions) ] # Process all UAVs for uav in self.env_agents: self.simpy_env.process( uav.sim() ) # Process all fires for fire in self.fires: self.simpy_env.process( fire.sim() ) done = simpy.AllOf(self.simpy_env, self.fire_extinguish_events) self.simpy_env.run(until = simpy.AnyOf(self.simpy_env, [done, self.simpy_env.timeout(MAX_SIMTIME)]) ) self.done = True if(True): for uav in self.env_agents: try: uav.action_event.interrupt() except RuntimeError: pass self.simpy_env.run(until = self.simpy_env.now*(1.0001)) assert sum([uav.get_reward() for uav in self.env_agents]) == 0, 'There were unaccounted for rewards' # Collect observations, actions, etc.. and return them observations = [ u.observations for u in self.env_agents] actions = [ u.actions for u in self.env_agents] rewards = [ u.rewards for u in self.env_agents] agent_infos = [ u.agent_infos for u in self.env_agents] env_infos = [ u.env_infos for u in self.env_agents] offset_t_sojourn = [ u.offset_t_sojourn for u in self.env_agents ] return observations, actions, rewards, agent_infos, env_infos, offset_t_sojourn
def _barrier(self):
"""
Grab and hold the rest of the ncq slots (already holding one)
"""
reqs = []
for i in range(self.ncq.ncq_depth - 1):
slot_req = self.ncq.slots.request()
reqs.append(slot_req)
yield simpy.AllOf(self.env, reqs)
for req in reqs:
self.ncq.slots.release(req)
def run(self):
while True:
req = self.new_req_func()
assert req.client_id == self.client_id
start = self.env.now
yield req.submit()
all_done = simpy.AllOf(self.env, req.all_done_list())
yield all_done
latency = self.env.now - start
self.num_reqs += 1
self.total_latency += latency
if latency > self.max_latency:
self.max_latency = latency
think_time = self.get_think_time()
if think_time != 0:
yield self.env.timeout(think_time)
def run_apps(self, num, comms_per_app=(500, 1000)):
"""
Start a number of apps to generate submission commands.
Args:
----
num (int): The number of apps to start.
comms_per_app: (int, int):
The number of commands in this range an app will generate.
If (a, b) is the range, the number of commands to generate
will be a <= x < b.
"""
events = []
for app_idx in range(num):
event_submitted = self.__env.event()
self.__env.process(
self.__app(app_idx, comms_per_app, event_submitted))
events.append(event_submitted)
self.__all_command_submitted = simpy.AllOf(self.__env, events)
def process_write_request(self, request: WriteRequest) -> int:
data = self.env.process(self.__data_plane(request))
control = self.env.process(self.__control_plane(request))
yield simpy.AllOf(self.env, [data, control])
self.__manager.answer_client_write(request)
def __control_plane(self, request: WriteRequest):
journal = self.env.process(self.__perform_journal_operation(request))
metadata = self.env.process(self.__propagate_metadata(request))
yield simpy.AllOf(self.env, [journal, metadata])
def reset_and_sim(self, policies):
self.simpy_env = simpy.Environment()
self.done = False
self.fire_extinguish_events = [
simpy.Event(self.simpy_env) for i in range(self.n_fires)
]
if self.fire_locations is True:
# Use presets
assert self.num_fire_clusters == 3, 'Only 3 clusters / fires per cluster implemented right now :('
assert self.n_fires / self.num_fire_clusters == 3, 'Only 3 clusters / fires per cluster implemented right now :('
R = np.array([[np.cos(120 * deg),
np.sin(-120 * deg)],
[np.sin(120 * deg),
np.cos(120 * deg)]])
f1 = np.reshape(np.array([-0.01, 1]), (2, 1))
f2 = np.reshape(np.array([0.01, 1]), (2, 1))
f3 = np.reshape(np.array([0, 1 - 0.02 * math.sin(60 * deg)]),
(2, 1))
fire_locations = [
f1, f2, f3,
R.dot(f1),
R.dot(f2),
R.dot(f3),
R.T.dot(f1),
R.T.dot(f2),
R.T.dot(f3)
]
fire_locations = [
np.reshape(f, (2, )).tolist() for f in fire_locations
]
self.fires = [
Fire(self, self.simpy_env, i, 1, fl)
for i, fl in enumerate(fire_locations)
]
else:
raise NotImplementedError
# we want to randomize
fire_locations = (2. * np.random.random_sample(
(self.n_fires, 2)) - 1.).tolist()
self.fires = [
Fire(self, self.simpy_env, i, fire_levels[i], fl)
for i, fl in enumerate(fire_locations)
]
if self.start_positions is not None:
self.env_agents = [
UAV(self, self.simpy_env, i, sp, sp, self.discount,
policies[i]) for i, sp in enumerate(self.start_positions)
]
else:
# we want to randomize
start_positions = (2. * np.random.random_sample(
(self.n_agents, 2)) - 1.).tolist()
self.env_agents = [
UAV(self, self.simpy_env, i, sp, sp, self.discount,
policies[i]) for i, sp in enumerate(start_positions)
]
# Process all UAVs
agent_events = []
for uav in self.env_agents:
agent_events.append(self.simpy_env.process(uav.sim()))
# Process all fires
for fire in self.fires:
self.simpy_env.process(fire.sim())
self.max_simtime_event = self.simpy_env.timeout(MAX_SIMTIME)
self.done_event = simpy.Event(self.simpy_env)
self.simpy_env.run(
until=simpy.AllOf(self.simpy_env, self.fire_extinguish_events)
| self.max_simtime_event)
self.done_event.succeed()
self.done = True
self.simpy_env.run(until=simpy.AllOf(self.simpy_env, agent_events))
rewards = [uav.get_reward() for uav in self.env_agents]
if sum(rewards) != 0:
print('There were unaccounted for rewards')
[print(r) for r in rewards]
raise RuntimeError
# Collect observations, actions, etc.. and return them
observations = [u.observations for u in self.env_agents]
actions = [u.actions for u in self.env_agents]
rewards = [u.rewards for u in self.env_agents]
agent_infos = [u.agent_infos for u in self.env_agents]
env_infos = [u.env_infos for u in self.env_agents]
offset_t_sojourn = [u.offset_t_sojourn for u in self.env_agents]
return observations, actions, rewards, agent_infos, env_infos, offset_t_sojourn